2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) 2018
DOI: 10.1109/isgteurope.2018.8571819
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Short-Term Forecasting in Electric Power Systems Using Artificial Neural Networks

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“…Also, in PV power forecasting, they become popular due to easy-to-use implementation and acceptable performance. The most popular methods, according to [4], to predict PV power are Artificial Neural Networks (ANNs) [5], [6], [7] and Support Vector Regression (SVR) [8], [9], [10]. In spite of the good performance of proposed methods, the majority of them rely on weather predictions (solar irradiation prediction, air temperature prediction, cloud coverage, etc.).…”
Section: Introductionmentioning
confidence: 99%
“…Also, in PV power forecasting, they become popular due to easy-to-use implementation and acceptable performance. The most popular methods, according to [4], to predict PV power are Artificial Neural Networks (ANNs) [5], [6], [7] and Support Vector Regression (SVR) [8], [9], [10]. In spite of the good performance of proposed methods, the majority of them rely on weather predictions (solar irradiation prediction, air temperature prediction, cloud coverage, etc.).…”
Section: Introductionmentioning
confidence: 99%